what does research tell us about the use of multitasking

Multitasking as a choice: a perspective

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• Published: 30 October 2017
• Volume 82 , pages 12–23, ( 2018 )

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• Laura Broeker   ORCID: orcid.org/0000-0001-7552-1060 1   na1 ,
• Roman Liepelt 1 ,
• Edita Poljac 2 ,
• Stefan Künzell 4 ,
• Harald Ewolds 4 ,
• Rita F. de Oliveira 3 &
• Markus Raab 1 , 3   na1  

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Performance decrements in multitasking have been explained by limitations in cognitive capacity, either modelled as static structural bottlenecks or as the scarcity of overall cognitive resources that prevent humans, or at least restrict them, from processing two tasks at the same time. However, recent research has shown that individual differences, flexible resource allocation, and prioritization of tasks cannot be fully explained by these accounts. We argue that understanding human multitasking as a choice and examining multitasking performance from the perspective of judgment and decision-making (JDM), may complement current dual-task theories. We outline two prominent theories from the area of JDM, namely Simple Heuristics and the Decision Field Theory, and adapt these theories to multitasking research. Here, we explain how computational modelling techniques and decision-making parameters used in JDM may provide a benefit to understanding multitasking costs and argue that these techniques and parameters have the potential to predict multitasking behavior in general, and also individual differences in behavior. Finally, we present the one-reason choice metaphor to explain a flexible use of limited capacity as well as changes in serial and parallel task processing. Based on this newly combined approach, we outline a concrete interdisciplinary future research program that we think will help to further develop multitasking research.

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Kelvin F. H. Lui & Alan C.-N. Wong

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Acknowledgements

We would like to thank the Department of Performance Psychology of the German Sport University Cologne for their helpful comments.

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Laura Broeker and Markus Raab contributed equally to this work.

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German Sport University, Am Sportpark Müngersdorf 6, 50933, Cologne, Germany

Laura Broeker, Roman Liepelt & Markus Raab

University of Freiburg, Engelbergerstr. 41, 79085, Freiburg, Germany

Edita Poljac

London South Bank University, 103 Borough Road, London, SE1 0AA, UK

Rita F. de Oliveira & Markus Raab

University of Augsburg, Universitätsstraße 2, 86159, Augsburg, Germany

Stefan Künzell & Harald Ewolds

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Correspondence to Laura Broeker .

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This research was funded by a Grant within the Priority Program, SPP 1772 from the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), Laura Broeker and Markus Raab were funded by Grant no.: RA 940/17-1, Roman Liepelt was funded by and LI 2115/2-1 Stefan Künzell and Harald Ewolds were funded by Grant no.: KU 1557/3-1, and Edita Poljac was supported by the Grant no.: KI 1388-/7-1.

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Broeker, L., Liepelt, R., Poljac, E. et al. Multitasking as a choice: a perspective. Psychological Research 82 , 12–23 (2018). https://doi.org/10.1007/s00426-017-0938-7

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DOI : https://doi.org/10.1007/s00426-017-0938-7

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• Published: 08 November 2022

Knowledge generalization and the costs of multitasking

• Kelly G. Garner 1 , 2 &
• Paul E. Dux   ORCID: orcid.org/0000-0002-4270-2583 1  

Nature Reviews Neuroscience volume  24 ,  pages 98–112 ( 2023 ) Cite this article

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Humans are able to rapidly perform novel tasks, but show pervasive performance costs when attempting to do two things at once. Traditionally, empirical and theoretical investigations into the sources of such multitasking interference have largely focused on multitasking in isolation to other cognitive functions, characterizing the conditions that give rise to performance decrements. Here we instead ask whether multitasking costs are linked to the system’s capacity for knowledge generalization, as is required to perform novel tasks. We show how interrogation of the neurophysiological circuitry underlying these two facets of cognition yields further insights for both. Specifically, we demonstrate how a system that rapidly generalizes knowledge may induce multitasking costs owing to sharing of task contingencies between contexts in neural representations encoded in frontoparietal and striatal brain regions. We discuss neurophysiological insights suggesting that prolonged learning segregates such representations by refining the brain’s model of task-relevant contingencies, thereby reducing information sharing between contexts and improving multitasking performance while reducing flexibility and generalization. These proposed neural mechanisms explain why the brain shows rapid task understanding, multitasking limitations and practice effects. In short, multitasking limits are the price we pay for behavioural flexibility.

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Acknowledgements

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement no. 796329 awarded to K.G.G. and ARC Discovery Projects grants DP180101885 and DP210101977 awarded to P.E.D. The authors thank D. Lloyd for his work on the graphical representations of the concepts in this Perspective. The authors also thank C. Nolan, H. Bowman, J. Mattingley, Y. Wards and A. Renton for providing helpful feedback and insightful commentary on previous drafts.

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Garner, K.G., Dux, P.E. Knowledge generalization and the costs of multitasking. Nat Rev Neurosci 24 , 98–112 (2023). https://doi.org/10.1038/s41583-022-00653-x

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How Multitasking Affects Productivity and Brain Health

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Amy Morin, LCSW, is a psychotherapist and international bestselling author. Her books, including "13 Things Mentally Strong People Don't Do," have been translated into more than 40 languages. Her TEDx talk,  "The Secret of Becoming Mentally Strong," is one of the most viewed talks of all time.

Gpointstudio / Getty Images

• Multitasking and Productivity

Brain Function in Multitaskers

• Break the Habit

Frequently Asked Questions

What is multitasking.

Multitasking involves working on two or more tasks simultaneously, switching back and forth from one thing to another, or performing a number of tasks in rapid succession.

Is multitasking a good thing? While multitasking seems like a great way to get a lot done at once, research has shown that our brains are not nearly as good at handling multiple tasks as we like to think they are. In fact, some research suggests that multitasking can actually hamper your productivity by reducing your comprehension, attention, and overall performance.

What is it that makes multitasking such a productivity killer? It might seem like you are accomplishing multiple things at the same time, but what you are really doing is quickly shifting your attention and focus from one thing to the next. Switching from one task to another may make it difficult to tune out distractions and can cause mental blocks that can slow you down.

Examples of Multitasking

• Starting two projects at the same time
• Listening to the radio while driving to work
• Talking on the phone while typing an assignment
• Watching television while responding to work emails
• Scrolling through social media while in a meeting
• Listening to a person talk while writing a to-do list

How Multitasking Hampers Productivity

Multitasking takes a serious toll on productivity . Our brains lack the ability to perform multiple tasks at the same time—in moments where we think we're multitasking, we're likely just switching quickly from task to task. Focusing on a single task is a much more effective approach for several reasons.

Multitasking Is Distracting

Multitaskers may feel more distracted than people who focus on one task at a time. This makes sense when you consider that, by habit, multitaskers constantly refocus on a new task, effectively distracting themselves from their original assignment.

Some research suggests that multitaskers are more distractible, and they may have trouble focusing their attention even when they're not working on multiple tasks at once.

Other research shows that while there may be a connection between multitasking and distraction, that link is smaller than originally thought and varies quite a bit from person to person.

Multitasking Slows You Down

While it may seem contrary to popular belief, we tend to work slower and less efficiently when we multitask. Multitasking leads to what psychologists call "task switch costs," or the negative effects that come from switching from task to task. We encounter task switch costs (like a slower working pace) because of the increased mental demand that's associated with jumping from one thing to another.

Changing our focus also keeps us from relying on automatic behaviors to finish tasks quickly. When we're focused on a single task that we've done before, we can work on "autopilot," which frees up mental resources. Switching back and forth bypasses this process, and we tend to work more slowly as a result.

Multitasking Impairs Executive Function

Multitasking is managed by executive functions in the brain . These control and manage cognitive processes and determine how, when, and in what order certain tasks are performed. There are two stages to the executive control process:

• Goal shifting : Deciding to do one thing instead of another
• Rule activation : Changing from the rules for the previous task to the rules for the new task

Moving through these stages may only add a few tenths of a second, but it can start to add up when people switch back and forth repeatedly. This might not be a big deal when you are folding laundry and watching television at the same time.

However, if you are in a situation where safety or productivity is important, such as when you are driving in heavy traffic, even small amounts of time can prove critical.

Multitaskers Make Mistakes

Multitasking may lower your performance and make you more prone to making mistakes. Research has shown that students who multitask in class tend to have lower GPAs (and, if they continue multitasking at home, they often take longer to finish their homework).

Adults may also experience lower performance while multitasking. One 2018 study found that older adults were likely to make more mistakes while driving if they were multitasking.

Doing several different things at once can impair cognitive ability , even for people who multitask frequently. In fact, research suggests that people tend to overestimate their ability to multitask, and the people who engage in this habit most frequently often lack the skills needed to be effective at it.

Chronic multitaskers tend to show more impulsivity than their peers, and they may be more likely to downplay possible risks associated with tackling multiple things at once. They also seem to show lower levels of executive control and are often distracted easily.

Limited cognitive resources may be involved in this phenomenon. Several networks in the brain interact to guide our behavior whenever we set out to complete a task. This behavior includes:

• Setting a goal
• Identifying the information we need to achieve it
• Disregarding irrelevant distractions

When we try to engage in this process for multiple tasks at once, it can lead to cognitive errors. We might fail to disregard irrelevant information, for instance, which would lead to more distraction.

The research isn't clear on the exact relationship between multitasking and brain function. It's possible that chronic multitasking changes the brain over time, leading to more distractibility and problems with focus, or it may be that people with these traits are more likely to multitask in the first place.

Teens and Multitasking

The negative impact of chronic, heavy multitasking might be particularly detrimental to adolescent minds. At this age, brains are busy forming important neural connections. Spreading attention so thin and constantly being distracted by different streams of information might have a serious, long-term, negative impact on how these connections form.

Media Multitasking

Some research suggests that people who engage in media multitasking (using more than one form of media or type of technology at once) might be better at integrating visual and auditory information.

In one study, participants between the ages of 19 and 28 were asked to complete questionnaires regarding their media usage. The participants then completed a visual search task both with and without a sound to indicate when an item changed color.

Heavy multitaskers performed better on the search when the sound was presented, indicating that they were more adept at integrating the two sources of sensory information . Conversely, heavy multitaskers performed worse than light/medium multitaskers when the tone was not present.

Break the Multitasking Habit

If you feel like multitasking is negatively impacting your life, it is possible to make some changes that will increase your productivity and efficiency. Next time you find yourself multitasking, take a quick assessment of the various things you are trying to accomplish. Then, determine which task you need to focus on first. Try to:

• Limit the number of things you juggle at any given time to just one task . If you do need to work on multiple things at once, try to combine something automatic, like folding laundry, with something that requires more focus, like having a conversation.
• Use the "20-minute rule." Instead of constantly switching between tasks, try to fully devote your attention to one task for 20 minutes before switching to the other.
• Batch your tasks . If you're having trouble resisting the urge to check your email or engage in another distracting task, schedule a set time in your day to tackle it. By batching similar tasks together and setting a time to handle them, you can free your mind up to focus on something else.
• Limit distractions . This may mean seeking out a quieter place to work, switching your phone off, and turning off notifications and alarms.
• Practice mindfulness . Adding mindfulness to your daily routine may help you notice the times when you're multitasking. Mindfulness can also improve your ability to focus and pay attention to one thing at a time.

Working on one task at a time may help you become more productive and it may make each task more enjoyable.

Yes, it can be. Multitasking may reduce your ability to focus, increase feelings of stress, and exacerbate impulsiveness. It can also worsen your performance at work or school, which can lead to further negative feelings and anxiety.

It means that, like most of us, their brain isn't wired to work on multiple complex tasks simultaneously. We perform much better when we focus fully on one thing at a time.

You should consider whether or not you're really able to multitask before adding it to your resume. We have a tendency to overestimate our ability to multitask, and even people who think they're skilled in this area often make mistakes or work inefficiently.

Jeong S-H, Hwang Y. Media multitasking effects on cognitive vs. attitudinal outcomes: A meta-analysis . Hum Commun Res . 2016;42(4):599-618. doi:10.1111/hcre.12089

Madore KP, Wagner AD. Multicosts of multitasking . Cerebrum . 2019;2019:cer-04-19.

Moisala M, Salmela V, Hietajärvi L, et al. Media multitasking is associated with distractibility and increased prefrontal activity in adolescents and young adults . NeuroImage . 2016;134:113-121. doi:10.1016/j.neuroimage.2016.04.011

Wiradhany W, Koerts J. Everyday functioning-related cognitive correlates of media multitasking: A mini meta-analysis . Media Psychol . 2021;24(2):276-303. doi:10.1080/15213269.2019.1685393

Rubinstein JS, Meyer DE, Evans, JE. Executive control of cognitive processes in task switching .  J Exp Psychol Human. 2001;27(4):763-797. doi:10.1037/0096-1523.27.4.763

Bellur S, Nowak KL, Hull KS. Make it our time: In class multitaskers have lower academic performance . Comput Hum Behav . 2015;53:63-70. doi:10.1016/j.chb.2015.06.027

Wechsler K, Drescher U, Janouch C, Haeger M, Voelcker-Rehage C, Bock O. Multitasking during simulated car driving: A comparison of young and older persons . Front Psychol . 2018;0. doi:10.3389/fpsyg.2018.00910

Sanbonmatsu DM, Strayer DL, Medeiros-Ward N, Watson JM. Who multi-tasks and why? Multi-tasking ability, perceived multi-tasking ability, impulsivity, and sensation seeking . PLOS ONE . 2013;8(1):e54402. doi:10.1371/journal.pone.0054402

Uncapher MR, Lin L, Rosen LD, et al. Media multitasking and cognitive, psychological, neural, and learning differences . Pediatrics . 2017;140(Supplement 2):S62-S66. doi:10.1542/peds.2016-1758D

Lui KFH, Wong AC-N. Does media multitasking always hurt? A positive correlation between multitasking and multisensory integration . Psychon Bull Rev . 2012;19(4):647-653. doi:10.3758/s13423-012-0245-7

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

March 1, 2012

12 min read

Top Multitaskers Help Explain How Brain Juggles Thoughts

The discovery of multitasking masterminds is revealing how the brain works when it strives to do several things at once

By David L. Strayer & Jason M. Watson

“Any man who can drive safely while kissing a pretty girl is simply not giving the kiss the attention it deserves,” Albert Einstein is purported to have said. The quote acknowledges a fundamental characteristic of human attention. Sometimes there simply is not enough of it to go around. Never mind the buzzes and beeps of every new text message and e-mail, distracting as they may be. The pressures to be supportive family members, lifelong learners, chiseled athletes and professional leaders make multitasking nearly irresistible. You can almost hear our collective inner monologue: there must be a way to trick time, to coerce that lengthy to-do list to start shrinking twice if not three times as fast. Yet effective multitasking is a myth. So, too, is the idea that members of the “multitasking generation,” who grew up with video games, smart phones and e-readers, can somehow concentrate on several things at once. In fact, research indicates that frequent multitaskers are often the worst at it.

That multitasking compromises performance  has been known for decades. Only now, however, are we beginning to identify some of the personality traits most commonly associated with the most flagrant job jugglers. To our surprise, we have also discovered that a small fraction of the participants in our studies appear to multitask with ease, performing cognitive feats we had not thought possible. These unique individuals have not only given us new insight into the neural mechanisms for managing multiple mental activities, they are also forcing us to rethink our theories of attention.

Know Your Limits The human mind’s limited capacity for attention became strikingly apparent with the growth of aviation during World War II. As the task of piloting an airplane increased in complexity, the amount of information that the pilot was required to process also grew—and so did the number of airplane accidents unrelated to mechanical failures. The pioneering psychologist Donald Broadbent set out to investigate whether pilots were able to take in all the information displayed to them. Through his experiments, Broadbent found that the mind of a pilot could take in only a limited number of signals. This premise of finite attention is now a cornerstone for contemporary cognitive neuroscience, and today it is well accepted that attention is limited in capacity and can be flexibly allocated among concurrent tasks.

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By this theory, however, devoting more attention to one activity necessarily implies taking it away from others. Attention is thought to amplify some signals and suppress others, two processes known as facilitation and inhibition. If your brain were a dashboard, facilitation and inhibition would be knobs that turn up the volume on relevant stimuli and tamp down extraneous sensations. Tuning attention appropriately is key to healthy cognition, and several psychological disorders stem from the failure to do so, either from difficulties amplifying the appropriate input from your eyes, ears and other senses or from trouble suppressing unimportant details of the environment. In some cases, excessive multitasking may even exacerbate attention-related psychological disorders.

For the past decade our laboratory has been investigating the phenomenon by examining how we balance driving and talking on a cell phone, a common if ill-advised habit of many people. The findings are clear: our performance deteriorates drastically when we attempt to focus on more than one task at a time. Although our interest is in higher-level cognitive activities that compete for attention, even simple acts such as walking and chewing gum can be impaired with sufficient cognitive load. In one classic YouTube video, a woman is caught on camera composing a text message on her cell phone while walking through a mall—until she tumbles headfirst into a water fountain. The stakes can be much higher when driving while maintaining a cell-phone conversation.

Bolstering the theory of a limited attention span, scientists have observed that cell-phone drivers’ reactions are slower, they have difficulty staying in their lane and maintaining appropriate following distance, and they are more likely to run red lights and miss other important details in the driving environment. We recently conducted an observational study of 56,000 drivers as they approached an intersection where they were required to come to a complete stop. We found that drivers talking on their cell phone were more than twice as likely to fail to stop appropriately.

At any given time during the day, about one in 10 individuals are both on the road and on the phone. Intersection violations are potentially hazardous events, so it is alarming to see that such a common behavior is associated with this level of impairment. In fact, we have reviewed a number of legal cases where a driver talking on a cell phone failed to notice a red traffic light and proceeded through the intersection, causing an accident that resulted in serious injuries or fatalities. Understanding when we can and cannot multitask is not just an academic exercise—it is a matter of life and death.

Driven to Distraction To study distracted driving in finer detail, we monitored participants using a realistic driving simulator. Using this device for a study in 2006, we found that the crash risk for those using a cell phone to talk or text often exceeds the level observed with drivers who are at the legal limit of alcohol intoxication.

Also using a driving simulator, we observed individuals’ eye movements and the corresponding brain activity through electrodes attached to the scalp. We found that drivers failed to notice up to half of the items that they looked at, and we confirmed that they reacted substantially more slowly to the information that they did detect.

In research published in 2003 and 2007, we tracked participants’ gaze to note what items they looked at and then quizzed subjects later about what they recalled observing. Their memory for the items their eyes fell on was only half as good while they were talking on a cell phone as when they were not distracted by the phone. A follow-up study published in 2007 found that this pattern was observed with both highly relevant items, such as a child standing on a sidewalk, and with less important landmarks, such as a billboard alongside the road. In other words, the brain does not prioritize information by its importance when deciding what is “lost” while the driver is on the phone. Lapses of attention essentially rendered the drivers partially blind to significant details directly in their gaze.

To establish that cell phones induce a form of inattention blindness, we again used electrodes on the scalp to compare the brain signals associated with the detection of illuminated brake lights on the vehicle in front of the driver. We measured the drivers’ brain activity both when they were talking on a hands-free cell phone and when they were not distracted by such use.

A particularly interesting component of these brain waves, known as the P300, is a signal that is sensitive to how much attention a person is paying to a specific stimulus. The amplitude of the P300 signal increases as more attention is allocated to a task. When drivers were talking on their cell phone, we found that the amplitude of the P300 was cut in half—a drop that reflects their decreased focus on the task of driving. The reduction in the P300 explains why drivers often fail to detect and react to events in the driving environment. Their brain is busy processing the conversation and not what they are looking at through the windshield.

Because both handheld and hands-free cell phones cause equivalent interference, it establishes that this is a form of cognitive distraction, as opposed to, say, a visual distraction that draws the driver’s eyes from the road or a manual distraction that compels the driver to remove his or her hands from the wheel. Even with eyes on the road and both hands on the wheel, the individual is impaired.

This finding has implications for a recent trend in state legislation. Many states have implemented laws prohibiting the use of handheld phones but permitting hands-free cell phones. Statistics from the Highway Loss Data Institute, a nonprofit road safety research group, indicate that such legislation has not improved traffic safety. More important, our studies suggest that the level of cognitive distraction is equivalent for both kinds of cell-phone use. These results also imply that computer-based speech-recognition systems currently being installed in vehicles are not likely to eliminate the problem.

Even so, not all distractions are created equal. When comparing the effects of being on the phone with chatting with another passenger in the car, for example, we found that the passenger and driver adjusted their conversation based on driving demands. The passenger also assisted by noting hazards and reminding the driver of their navigation goal. This real-time adjustment in the dialogue to road conditions was not observed with cell-phone conversations. In fact, drivers chatting with a passenger had no trouble getting to their destination—in the case of our experiment, a roadside rest stop—whereas half of the drivers on a cell phone completely missed their exit.

Practice Makes Imperfect Perhaps, you might argue, these individuals were simply not accustomed to the rigors of driving while on the phone. In this case at least, practice does not seem to lead to great gains in performance. When we compared drivers who frequently used cell phones with those who did so less often, we did not find that the first group was less impaired, and extensive laboratory practice also did not appear to help.

The reality might actually be even more dire, however, than a straightforward lack of improvement. In 2009 Clifford Nass of Stanford University and his colleagues assessed individuals on the degree to which they engaged in multitasking and timed how long it took them to switch among tasks, specifically between classifying a digit as odd or even and judging whether a letter is a consonant or a vowel. They found a negative correlation between the two measures, whereas higher self-reported levels of media multitasking were associated with longer times for people to switch between classifying digits and letters. It appears that trying to do several things at once actually diminishes your skills.

In a recent collaboration with social psychologist David Sanbomnatsu, our colleague at the University of Utah, we asked more than 300 participants to rate the frequency of their multitasking and their perceived ability to do so (relative to the average college student) and then asked them to complete a multitasking test. In the exam, participants memorized an ordered list of items and tried to keep them in mind while simultaneously solving math problems. Using standard questionnaires, we also rated how impulsive and sensation-seeking the participants were.

Our data all showed the same pattern: people who were high in real-world multitasking had lower working-memory capacity, were more impulsive and sensation-seeking, and tended to rate their own ability to multitask as higher than average. That is, their perceived ability and actual ability to multitask were inversely related. This work suggests that overconfidence, rather than skill, drives the proliferation of multitasking.

Whether doing several things at once depletes working memory or whether those who formed a habit of multitasking already were less adept at mentally manipulating various pieces of information concurrently is not yet known, although we suspect that both might be true. We have some early evidence that multitasking causes a kind of cognitive depletion and that “unplugging” has restorative properties.

As for what might feed the underlying motivation to multitask, one possibility, as suggested by lab studies done in 2007 by Stephen J. Payne of the University of Bath in England and his colleagues, is that individuals switching among tasks are seeking to increase the time spent on the activity that produces the most reward. That observation could well match our reports that heavy multitaskers tend to be sensation-seeking. Whatever the cause, a divided attention appears to impede performance rather than assisting it.

The inability to overcome these costs is particularly salient when it comes to reacting to an unexpected event, such as a child running out into the street. But as we were about to learn, not everybody fits that mold.

Search for Supertaskers We found our first exception to the rule completely by accident. We were comparing our study participants’ scores on different tasks, such as driving alone, talking on a hands-free phone alone, and doing both concurrently. After going through the data, however, we identified one unusual subject who had virtually identical scores for doing either just one or both activities. After checking and rechecking the data, we realized that this person was multitasking in ways we had not thought possible. We continued our data collection in search of more such anomalies. After testing approximately 700 people, we have identified 19 people so far who meet the “supertasker” criteria, or about 2.5 percent. These individuals all ranked among the top 25 percent when doing a single task, and their performance did not deteriorate when completing two assignments at once.

To identify the neural regions that support supertaskers’ extraordinary multitasking ability, we used functional MRI. We scanned 16 of our supertaskers as well as a group of subjects who matched them in their single-task scores, working-memory capacity, gender and age, among other measures. Because the driving simulator and the MRI facilities are incompatible technologies, we switched to a computerized multitasking test that required participants to concurrently maintain and manipulate separate visual and auditory streams of information.

We saw significant differences in the patterns of neural activation of supertaskers and the control group. Supertaskers showed less activity at the more difficult levels of the multitasking test. For most people, a tougher challenge recruits more resources in the brain, but supertaskers showed little or no change in brain activity as the task became more demanding, suggesting that somehow these individuals can achieve greater efficiencies and, along with it, higher performance. Our supertaskers seem to have the “right stuff,” keeping their brains cool under a heavy load, just as fighter pilots are reported to do in demanding situations. Because our studies controlled for working-memory capacity, we know that working memory is important but not sufficient to account for superior multitasking abilities.

Supertaskers differed most strikingly from control subjects in three frontal brain areas that earlier neuropsychological research on multitasking had flagged: the frontopolar prefrontal cortex, dorsolateral prefrontal cortex and the anterior cingulate cortex. For us, the most intriguing brain region that differentiated supertaskers from controls was the frontopolar cortex. Comparative studies with humans and great apes indicate that this area is relatively larger and more richly interconnected in humans, whereas other frontal cortical areas are more equivalent in size and connectivity. The emergence of humans’ multitasking ability, however flawed, might be a relatively recent evolutionary change in hominid brains, helping to distinguish humans from other animals. In addition, neuropsychological patients with more extensive frontopolar damage have been shown to be more impaired in multitasking. Now we know that high levels of efficient processing in these regions support extraordinary multitasking ability, bringing us one step closer to finally developing a model of how the brain multitasks.

The examination of individual differences in multitasking ability is a relatively new enterprise, however. Whether supertaskers are just an extreme on a continuum or are qualitatively different is still an open question.

The Multitasking Advantage To tease out what distinguishes these brains, we are now looking for differences in the connections among regions in the supertasking brain as well as hunting for unique features in their genetics, either of which could lead to more efficient processing for these individuals. Variants of one particular gene, catechol-O-methyltransferase ( COMT ), for example, are associated with differences in working memory, executive attention and a slight predisposition to a broad number of psychological disorders.

One reason to examine this gene is that its variants alter how efficiently the neurotransmitter dopamine can operate in the frontal cortex, which encompasses the brain regions that support multitasking. It is thought that lower COMT enzyme activity may result in greater availability of dopamine for binding at receptor sites in the frontal cortex. By sequencing the DNA in samples of our supertaskers’ blood or saliva, we have found preliminary evidence suggesting that these individuals possess a variant of COMT that leads to more efficient dopamine signaling in the regions of the brain supporting multitasking. We are still investigating whether the features of this gene might explain supertaskers’ superior powers of attention.

To expand our research, we will need to find more supertaskers. It is intriguing to consider where we might find them—that is, which occupations might ideally suit supertaskers. Pilots of high-performance aircraft are good candidates to be supertaskers. So, too, are high-end chefs who can cook several meals at the same time to perfection. Perhaps some of the star quarterbacks in the National Football League are supertaskers. Champion video gamers may also be a good bet, as are the elite doctors in hospital emergency rooms. All other things being equal, we suspect that supertaskers will rise to the top in any occupation that places a high demand on juggling various attention-demanding tasks at the same time.

Exploring why the supertasking mind excels where the rest of us fail might help us structure tasks so they do not overtax the brain’s abilities, such as using auditory cues in contexts where visual information is overwhelming. The research can also add more nuance to our understanding of attention-related psychiatric problems, including obsessive-compulsive disorder, thought disorders and attention-deficit hyperactivity disorder.

Given the rise of technology over the past few generations and the role it has played in making frequent multitasking possible, one might ponder the potential long-term consequences of a society that places such high value on this skill. Returning to Einstein’s observations on driving and kissing—or talking on a cell phone—the vast majority of us cannot multitask without significant costs. In the very distant future, supertaskers’ ability to better cope with multiple goals and information sources may be an increasingly adaptive feature in the evolution of our species.

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A decade of data reveals that heavy multitaskers have reduced memory, Stanford psychologist says

People who frequently engage with multiple types of media at once performed worse on simple memory tasks, according to the last decade of research. However, it’s still too soon to determine cause and effect, says psychology Professor Anthony Wagner.

The smartphones that are now ubiquitous were just gaining popularity when Anthony Wagner became interested in the research of his Stanford colleague, Clifford Nass, on the effects of media multitasking and attention. Though Wagner, a professor of psychology at Stanford University and director of the Stanford Memory Laboratory , wasn’t convinced by the early data, he recommended some cognitive tests for Nass to use in subsequent experiments. More than 11 years later, Wagner was intrigued enough to write a review on past research findings, published in Proceedings of the National Academy of Sciences , and contribute some of his own.

A decade’s worth of research has shown that people who frequently use many types of media at once performed significantly worse on simple memory tasks. (Image credit: Getty Images)

The paper , co-authored with neuroscientist Melina Uncapher of the University of California, San Francisco, summarizes a decade’s worth of research on the relationship between media multitasking and various domains of cognition, including working memory and attention. In doing that analysis, Wagner noticed a trend emerging in the literature: People who frequently use many types of media at once, or heavy media multitaskers, performed significantly worse on simple memory tasks.

Wagner spoke with Stanford Report to explain the findings from his review on media multitasking and cognition, and discuss why it’s premature to determine the impact of these results.

How did you become interested in researching media multitasking and memory?

I was brought into a collaboration with Cliff Nass, a Stanford faculty member in communication who passed away a few years ago, and his master’s student, Eyal Ophir. They had this question: With the explosion of media technologies that has resulted in there being multiple simultaneous channels available that we can switch between, how might this relate to human cognition? Eyal and Cliff would come chat with me about their early findings and – I have to say – I thought it was complete hooey. I was skeptical. But, after a few experiments, the data were increasingly pointing to a link between media multitasking and attention. Their findings struck me as potentially important given the way we’re living as humans in this attention economy. Years later, as a memory scientist my interests continued to grow. Given that attention and cognitive control are so fundamental for memory, I wanted to see if there was a relationship between media multitasking and memory.

How do you define media multitasking, and can you give hypothetical examples of people that would be “heavy” and “light” media multitaskers?

Well, we don’t multitask. We task switch. The word “multitasking” implies that you can do two or more things at once, but in reality our brains only allow us to do one thing at a time and we have to switch back and forth.

Heavy media multitaskers have many media channels open at once and they switch between them. A heavy media multitasker might be writing an academic paper on their laptop, occasionally checking the Stanford basketball game on TV, responding to texts and Facebook messages, then getting back to writing – but then an email pops up and they check it. A light media multitasker would only be writing the academic paper or may only switch between a couple of media. They may turn off Wi-Fi, put away their phone or change their settings so they only get notified every hour. Those are some extreme examples, but they provide a sense of how people differ in their media use. Moreover, because our media landscape has continued to accelerate and change, those who are considered a heavy or light media multitasker today may not be the same as those a decade ago.

How do scientists assess someone’s memory?

There are many forms of memory, and thus many ways of probing memory in the lab. For working memory – the ability to keep a limited amount of information active in mind – we often use simple short-delay memory tasks. For example, in one test we show a set of oriented blue rectangles, then remove them from the screen and ask the subject to retain that information in mind. Then we’ll show them another set of rectangles and ask if any have changed orientation. To measure memory capacity, we do this task with a different number of rectangles and determine how performance changes with increasing memory loads. To measure the ability to filter out distraction, sometimes we add distractors, like red rectangles that the subjects are told to ignore.

What overall trends did you notice when you were looking through the literature to write this review?

In about half of the studies, the heavy media multitaskers are significantly underperforming on tasks of working memory and sustained attention. The other half are null results; there’s no significant difference. It strikes me as pretty clear that there is a negative relationship between media multitasking and memory performance – that high media multitasking is associated with poor performance on cognitive memory tasks. There’s not a single published paper that shows a significant positive relationship between working memory capacity and multitasking.

In the review we noticed an interesting potential emerging story. One possibility is that reduced working memory occurs in heavy media multitaskers because they have a higher probability of experiencing lapses of attention. When demands are low, they underperform. But, when the task demands are high, such as when the working memory tasks are harder, there’s no difference between the heavy and light media multitaskers. This observation, combined with the negative relationship between multitasking and performance on sustained attention tasks, prompted us to start looking at intrasubject variability and moment-to-moment fluctuations in a person’s ability to use task goals to direct attention in a sustained manner.

How do these findings affect how people should engage with media, or should they at all?

I would never tell anyone that the data unambiguously show that media multitasking causes a change in attention and memory. That would be premature. It’s too early to definitively determine cause and effect.

One could choose to be cautious, however. Many of us have felt like our technology and media are controlling us – that email chime or text tone demands our attention. But we can control that by adopting approaches that minimize habitual multitasking; we can decide to be more thoughtful and reflective users of media.

That said, multitasking isn’t efficient. We know there are costs of task switching. So that might be an argument to do less media multitasking – at least when working on a project that matters academically or professionally. If you’re multitasking while doing something significant, like an academic paper or work project, you’ll be slower to complete it and you might be less successful.

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Multitasking, social media and distraction: Research review

2013 research review of major studies relating to multitasking and distraction, with an emphasis on young people and social media.

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by John Wihbey, The Journalist's Resource July 11, 2013

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Over the past decade, academic research has increasingly examined issues of multitasking and distraction as people try to squeeze more activities into their busy lives. Prior to the Internet age, some cognition science research focused on how behavior might be better understood, improved and made more efficient in business, hospital or other high-pressure settings. But as digital technology has become ubiquitous in many people’s daily routines — and as multitasking has become a “lifestyle” of sorts for many younger people — researchers have tried to assess how humans are coping in this highly connected environment and how “chronic multitasking” may diminish our capacity to function effectively.

In 2009, a Stanford University study published in the Proceedings of the National Academy of Sciences , “Cognitive Control in Media Multitaskers,” provided some of the most definitive evidence yet of the perils of multitasking in a digital age. It was subsequently cited hundreds of times and raised many unanswered questions and myriad research directions to pursue . But one of the study’s co-authors, Clifford Nass, notes that scholarship has remained firm in the overall assessment: “The research is almost unanimous, which is very rare in social science, and it says that people who chronically multitask show an enormous range of deficits. They’re basically terrible at all sorts of cognitive tasks, including multitasking.”

Scholars from many different disciplines are designing experimental and observational studies of all kinds to assess how we may be changing our mental habits. As the Pew Internet & American Life Project has found in conversations with experts on the subject, the very idea of “multitasking” continues to be debated and refined. The topic has also produced important book-length meditations informed by research, such as Sherry Turkle’s Alone Together , Nicholas Carr’s The Shallows and William Powers’s Hamlet’s Blackberry .

Of particular interest to researchers have been the habits of, and outcomes for, young persons — the so-called “Net Generation” or “digital natives.” (New research from students themselves suggests a higher rate of “supertaskers” — those who claim to thrive while multitasking — among younger cohorts than has been previously reported.) Research in the past few years has focused on how social networking technologies such as Facebook might affect offline performance and learning. Survey research from institutions such as the Kaiser Family Foundation and Pew Research can also complement the academic studies on the way teens and Millennials are living highly connected lives.

Below are more than a dozen representative studies in these areas:

“Cognitive Control in Media Multitaskers” Ophira, Eyal; Nass, Clifford; Wagner, Anthony D. PNAS: Proceedings of the National Academy of Sciences , August 24, 2009. doi: 10.1073/pnas.0903620106.

Findings: The study used experiments to compare heavy media multitaskers to light media multitaskers in terms of their cognitive control and ability to process information…. When intentionally distracting elements were added to experiments, heavy media multitaskers were on average 77 milliseconds slower than their light media multitasker counterparts at identifying changes in patterns. In a longer-term memory test that invited participants to recall specific elements from earlier experiments, the high media multitaskers more often falsely identified the elements that had been used most frequently as intentional distracters. The researchers conclude that the experiments “suggest that heavy media multitaskers are distracted by the multiple streams of media they are consuming, or, alternatively, that those who infrequently multitask are more effective at volitionally allocating their attention in the face of distractions.” The findings raise profound, still-unanswered questions about human cognition in the future: “If the growth of multitasking across individuals leads to or encourages the emergence of a qualitatively different, breadth-biased profile of cognitive control, then the norm of multiple input streams will have significant consequences for learning, persuasion, and other media effects. If, however, these differences in cognitive control abilities and strategies stem from stable individual differences, many individuals will be increasingly unable to cope with the changing media environment.”

“Multitasking across Generations: Multitasking Choices and Difficulty Ratings in Three Generations of Americans” Carriera, L. Mark; Cheever, Nancy A.; Rosena, Larry D.; Beniteza, Sandra; Changa, Jennifer. Computers in Human Behavior , Vol. 25, Issue 2, March 2009, 483-489. http://dx.doi.org/10.1016/j.chb.2008.10.012.

Abstract: “This study investigated whether changes in the technological/social environment in the United States over time have resulted in concomitant changes in the multitasking skills of younger generations. One thousand, three hundred and nineteen Americans from three generations were queried to determine their at-home multitasking behaviors. An anonymous online questionnaire asked respondents to indicate which everyday and technology-based tasks they choose to combine for multitasking and to indicate how difficult it is to multitask when combining the tasks. Combining tasks occurred frequently, especially while listening to music or eating. Members of the ‘Net Generation’ reported more multitasking than members of ‘Generation X,’ who reported more multitasking than members of the ‘Baby Boomer’ generation. The choices of which tasks to combine for multitasking were highly correlated across generations, as were difficulty ratings of specific multitasking combinations. The results are consistent with a greater amount of general multitasking resources in younger generations, but similar mental limitations in the types of tasks that can be multitasked.”

“Supertaskers: Profiles in Extraordinary Multitasking Ability” Watson, Jason M.; Strayer, David L. Psychonomic Bulletin & Review , August 2010, Vol. 17, Issue 4, 479-485.

Abstract: “Theory suggests that driving should be impaired for any motorist who is concurrently talking on a cell phone. But is everybody impaired by this dual-task combination? We tested 200 participants in a high-fidelity driving simulator in both single- and dual-task conditions. The dual task involved driving while performing a demanding auditory version of the operation span (OSPAN) task. Whereas the vast majority of participants showed significant performance decrements in dual-task conditions (compared with single-task conditions for either driving or OSPAN tasks), 2.5% of the sample showed absolutely no performance decrements with respect to performing single and dual tasks. In single-task conditions, these ‘supertaskers’ scored in the top quartile on all dependent measures associated with driving and OSPAN tasks, and Monte Carlo simulations indicated that the frequency of supertaskers was significantly greater than chance. These individual differences help to sharpen our theoretical understanding of attention and cognitive control in naturalistic settings.”

“Facebook and Texting Made Me Do it: Media-induced Task-switching while Studying” Rosen, Larry D.; Carrier, L. Mark; Cheever, Nancy A. Computers in Human Behavior , 2013, Volume, 948-958. doi: http://dx.doi.org/10.1016/j.chb.2012.12.001.

Abstract: “Electronic communication is emotionally gratifying, but how do such technological distractions impact academic learning? The current study observed 263 middle school, high school and university students studying for 15 minutes in their homes. Observers noted technologies present and computer windows open in the learning environment prior to studying plus a minute-by-minute assessment of on-task behavior, off-task technology use and open computer windows during studying. A questionnaire assessed study strategies, task-switching preference, technology attitudes, media usage, monthly texting and phone calling, social networking use and grade point average (GPA). Participants averaged less than six minutes on task prior to switching most often due to technological distractions including social media, texting and preference for task-switching. Having a positive attitude toward technology did not affect being on-task during studying. However, those who preferred to task-switch had more distracting technologies available and were more likely to be off-task than others. Also, those who accessed Facebook had lower GPAs than those who avoided it. Finally, students with relatively high use of study strategies were more likely to stay on-task than other students. The educational implications include allowing students short ‘technology breaks’ to reduce distractions and teaching students metacognitive strategies regarding when interruptions negatively impact learning.”

“Millennials Will Benefit and Suffer Due to Their Hyperconnected Lives” Anderson, Janna; Rainie, Lee. Pew Internet & American Life Project report, February 2013.

Abstract: “In a survey about the future of the Internet, technology experts and stakeholders were fairly evenly split as to whether the younger generation’s always-on connection to people and information will turn out to be a net positive or a net negative by 2020. They said many of the young people growing up hyperconnected to each other and the mobile Web and counting on the Internet as their external brain will be nimble, quick-acting multitaskers who will do well in key respects. At the same time, these experts predicted that the impact of networked living on today’s young will drive them to thirst for instant gratification, settle for quick choices, and lack patience. A number of the survey respondents argued that it is vital to reform education and emphasize digital literacy. A notable number expressed concerns that trends are leading to a future in which most people are shallow consumers of information, and some mentioned George Orwell’s 1984 or expressed their fears of control by powerful interests in an age of entertaining distractions.”

“No A 4 U: The Relationship between Multitasking and Academic Performance” Juncoa, Reynol; Cotten, Shelia R. Computers & Education , 2012, Vol. 59, Issue 2, September 2012, 505-514. doi: http://dx.doi.org/10.1016/j.compedu.2011.12.023.

Findings: The researchers examine how the use of Facebook — and engagement in other forms of digital activity — while trying to complete schoolwork was associated with college students’ grade point averages. Students gave the researchers permission to see their grades. The participant group was 64% female, and 88% were of traditional college age, 18 to 22 years old. The study’s findings include: During coursework, “students spent the most time using Facebook, searching for non-school-related information online, and emailing. While doing schoolwork outside of class, students reported spending an average of 60 minutes per day on Facebook, 43 minutes per day searching, and 22 minutes per day on email. Lastly, students reported sending an average of 71 texts per day while doing schoolwork.” The data suggest that “using Facebook and texting while doing schoolwork were negatively predictive of overall GPA.” However, “emailing, talking on the phone, and using IM were not related to overall GPA.”

“Media Multitasking is Associated with Symptoms of Depression and Social Anxiety” Becker, Mark W.;  Alzahabi, Reem; Hopwood, Christopher J. Cyberpsychology, Behavior, and Social Networking , February 2013, Vol. 16, Issue 2, 132-135. doi:10.1089/cyber.2012.0291.

Abstract: “We investigated whether multitasking with media was a unique predictor of depression and social anxiety symptoms. Participants (N=318) completed measures of their media use, personality characteristics, depression, and social anxiety. Regression analyses revealed that increased media multitasking was associated with higher depression and social anxiety symptoms, even after controlling for overall media use and the personality traits of neuroticism and extraversion. The unique association between media multitasking and these measures of psychosocial dysfunction suggests that the growing trend of multitasking with media may represent a unique risk factor for mental health problems related to mood and anxiety. Further, the results strongly suggest that future research investigating the impact of media use on mental health needs to consider the role that multitasking with media plays in the relationship.”

“The Impact of Engagement with Social Networking Sites (SNSs) on Cognitive Skills” Alloway, Tracy Packiam; Alloway, Ross Geoffrey. Computers in Human Behavior , Vol. 28, Issue 5, September 2012, 1748-1754. doi: http://dx.doi.org/10.1016/j.chb.2012.04.015.

Abstract: “The aim of the present study was to investigate the effect of social networking sites (SNSs) engagement on cognitive and social skills. We investigated the use of Facebook, Twitter and YouTube in a group of young adults and tested their working memory, attentional skills, and reported levels of social connectedness. Results showed that certain activities in Facebook (such as checking friends’ status updates) and YouTube (telling a friend to watch a video) predicted working memory test performance. The findings also indicated that Active and Passive SNS users had qualitatively different profiles of attentional control. The Active SNS users were more accurate and had fewer misses of the target stimuli in the first block of trials. They also did not discriminate their attentional resources exclusively to the target stimuli and were less likely to ignore distractor stimuli. Their engagement with SNS appeared to be exploratory and they assigned similar weight to incoming streams of information. With respect to social connectedness, participants’ self-reports were significantly related to Facebook use, but not Twitter or YouTube use, possibly as the result of greater opportunity to share personal content in the former SNS.”

“Media Use, Face-to-Face Communication, Media Multitasking and Social Well-Being Among 8- to 12-Year-Old Girls” Pea, Roy; Nass, Clifford; Meheula, Lyn; Rance, Marcus; Kumar, Aman; Bamford, Holden; Nass, Matthew; Simha, Aneesh; Stillerman, Benjamin; Yang, Steven; Zhou, Michael. Developmental Psychology , March 2012, Vol. 48, Issue 2, 327-336. doi: 10.1037/a0027030.

Findings: The researchers examined how digital media consumption and multitasking may impact social and cognitive development of ’tween girls. Media use included “video, video games, music listening … e-mailing/posting on social media sites, texting/instant messaging, and talking on phones/video chatting.” Researchers used data collected from nearly 3,5000 respondents to an online survey sponsored by Discovery Girls magazine in the summer of 2010. Major findings include: Watching videos, communicating online and media multitasking “were consistently associated with a range of negative socioemotional outcomes…. Face-to-face communication and online communication are not interchangeable.” Despite increased media use by ’tween girls, “no more than 10.1% of respondents ranked online friends more positively than in-person friends for even one item. Even heavy media users tended to derive … positive feelings principally from in-person friends.” Most media use had a neutral or slightly negative correlation with social well-being. In particular, watching videos was strongly associated with more negative feelings. However, “face-to-face communication was positively associated with feelings of social success [and] was consistently associated with a range of positive socioemotional outcomes.”

“Too Much Face and Not Enough Books: The Relationship between Multiple Indices of Facebook Use and Academic Performance” Junco, Reynol. Computers in Human Behavior , 2011, Vol. 28, Issue 1, 187-198.

Abstract: “Because of the social media platform’s widespread adoption by college students, there is a great deal of interest in how Facebook use is related to academic performance. A small number of prior studies have examined the relationship between Facebook use and college grade point average (GPA); however, these studies have been limited by their measures, sampling designs and failure to include prior academic ability as a control variable. For instance, previous studies used non-continuous measures of time spent on Facebook and self-reported GPA. This paper fills a gap in the literature by using a large sample ( N  = 1,839) of college students to examine the relationship among multiple measures of frequency of Facebook use, participation in Facebook activities, and time spent preparing for class and actual overall GPA. Hierarchical (blocked) linear regression analyses revealed that time spent on Facebook was strongly and significantly negatively related to overall GPA, while only weakly related to time spent preparing for class. Furthermore, using Facebook for collecting and sharing information was positively predictive of the outcome variables while using Facebook for socializing was negatively predictive.”

“Facebook and Academic Performance” Kirschner, Paul A.;Karpinski, Aryn C. Computers in Human Behavior , November 2010, Vol. 26, Issue 6, 1237-1245. doi: http://dx.doi.org/10.1016/j.chb.2010.03.024.

Abstract: “There is much talk of a change in modern youth — often referred to as digital natives or Homo Zappiens — with respect to their ability to simultaneously process multiple channels of information. In other words, kids today can multitask. Unfortunately for proponents of this position, there is much empirical documentation concerning the negative effects of attempting to simultaneously process different streams of information showing that such behavior leads to both increased study time to achieve learning parity and an increase in mistakes while processing information than those who are sequentially or serially processing that same information. This article presents the preliminary results of a descriptive and exploratory survey study involving Facebook use, often carried out simultaneously with other study activities, and its relation to academic performance as measured by self-reported Grade Point Average (GPA) and hours spent studying per week. Results show that Facebook users reported having lower GPAs and spend fewer hours per week studying than nonusers.”

“Perceived Academic Effects of Instant Messaging Use” Junco, Reynol; Cotton, Sheila R. Computers & Education , Vol. 56, Issue 2, February 2011, 370-378. doi: http://dx.doi.org/10.1016/j.compedu.2010.08.020.

Abstract: “College students use information and communication technologies at much higher levels and in different ways than prior generations. They are also more likely to multitask while using information and communication technologies. However, few studies have examined the impacts of multitasking on educational outcomes among students. This study fills a gap in this area by utilizing a large-sample web-based survey of college student technology usage to examine how instant messaging and multitasking affect perceived educational outcomes. Since multitasking can impede the learning process through a form of information overload, we explore possible predictors of academic impairment due to multitasking. Results of this study suggest that college students use instant messaging at high levels, they multitask while using instant messaging, and over half report that instant messaging has had a detrimental effect on their schoolwork. Higher levels of instant messaging and specific types of multitasking activities are associated with students reporting not getting schoolwork done due to instant messaging. We discuss implications of these findings for researchers studying the social impacts of technology and those in higher education administration.”

“Cognitive Pitfall! Videogame Players Are Not Immune to Dual-Task Costs” Donohue, S.E.; James, B.; Eslick, A.N.; Mitroff, S.R. Attention, Perception & Psychophysics , July 2012, Vol. 74, Issue 5, 803-809. doi: 10.3758/s13414-012-0323-y.

Findings: The researchers look at how gamers and non-gamers perform simultaneous tasks and whether serious gamers were better at multitasking than non-gamers. The researchers devised three simulations that measured driving speed and safety, multi-object tracking and image search skills. Each simulation had two versions: a single-track version involving only the simulation task; and a dual-track version in which participants were asked trivia questions while completing the simulation. The study’s findings include: “All of the participants … performed worse during the dual-task condition, and there were no differences in how they were affected.” None of the subjects, including both gamers and non-gamers, met the requirements to be classified as supertaskers. The authors suggest that “there are indeed limits to [gaming’s] benefits” and that gamers’ heightened powers of perception may be restricted to one task at a time. The researchers suggest that a gamer’s “heightened visual attention may come at the expense of the attentional resources available to other modalities” such as sound, and that these shortcomings may only emerge when faced with unfamiliar tasks. “This result demonstrates just how detrimental a concurrent distracting task can be,” the authors conclude. “Combined with other, previous evidence … this highlights how important it is for society to understand the limits of attentional processing.”

“Gender Differences in Multitasking Reflect Spatial Ability” Mäntylä, Timo. Psychological Science, April 2013, Vol. 24, No. 4, 514-520. doi: 10.1177/0956797612459660.

Abstract: “Demands involving the scheduling and interleaving of multiple activities have become increasingly prevalent, especially for women in both their paid and unpaid work hours. Despite the ubiquity of everyday requirements to multitask, individual and gender-related differences in multitasking have gained minimal attention in past research. In two experiments, participants completed a multitasking session with four gender-fair monitoring tasks and separate tasks measuring executive functioning (working memory updating) and spatial ability (mental rotation). In both experiments, males outperformed females in monitoring accuracy. Individual differences in executive functioning and spatial ability were independent predictors of monitoring accuracy, but only spatial ability mediated gender differences in multitasking. Menstrual changes accentuated these effects, such that gender differences in multitasking (and spatial ability) were eliminated between males and females who were in the menstrual phase of the menstrual cycle but not between males and females who were in the luteal phase. These findings suggest that multitasking involves spatiotemporal task coordination and that gender differences in multiple-task performance reflect differences in spatial ability.”

Tags: technology, youth, Facebook, research roundup

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John Wihbey

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Bilingualism as a Model for Multitasking

Because both languages of bilinguals are constantly active, bilinguals need to manage attention to the target language and avoid interference from the non-target language. This process is likely carried out by recruiting the executive function (EF) system, a system that is also the basis for multitasking. In previous research, bilinguals have been shown to outperform monolinguals on tasks requiring EF, suggesting that the practice using EF for language management benefits performance in other tasks as well. The present study examined 203 children, 8-11 years old, who were monolingual, partially bilingual, bilingual, or trilingual performing a flanker task. Two results support the interpretation that bilingualism is related to multitasking. First, bilingual children outperformed monolinguals on the conflict trials in the flanker task, confirming previous results for a bilingual advantage in EF. Second, the inclusion of partial bilinguals and trilinguals set limits on the role of experience: partial bilingual performed similarly to monolinguals and trilinguals performed similarly to bilinguals, suggesting that degrees of experience are not well-calibrated to improvements in EF. Our conclusion is that the involvement of EF in bilingual language processing makes bilingualism a form of linguistic multitasking.

Roughly half of the world's population is bilingual or multilingual, with many more in the process of becoming bilingual ( Bhatia & Ritchie, 2013 ). Thus, a significant portion of people regularly exist in a sustained and unique dual-language situation: Every act of language processing calls for the recruitment of mental resources to control attention to two (or possibly more) languages. We shall argue that this bilingual situation constitutes a special type of multitasking and that the consequences of this linguistic multitasking may have implications for understanding other dual task situations that children encounter in development.

There is substantial converging evidence that both languages in bilinguals are constantly active to some degree even if only one is supported by the environment (for review, see Kroll, Dussias, Bogulski, & Valdes-Kroff, 2012 ). Therefore, in order to ensure fluent language processing without intrusions from the unwanted language there needs to be a cognitive mechanism that controls attention to the two jointly activated systems and selects correctly for the context. The system generally attributed with this function is the executive control or executive function (EF) system ( Abutalebi & Green, 2008 ), a set of processes situated in the frontal lobes ( Stuss, 2011 ; Stuss & Benson, 1986 ). In an influential analysis of the construct, Miyake and colleagues ( Miyake et al., 2000 ; Miyake & Friedman, 2012 ) identified three core components of EF: (1) monitoring and mental set shifting, (2) updating and working memory, and (3) selective attention and inhibition. All these components are immature in infants and develop slowly across early childhood (e.g., Garon, Bryson, & Smith, 2008 ).

Central to this argument is the assumption that both languages are jointly activated, creating the need for a cognitive mechanisms to avoid intrusion even when bilinguals are in exclusively monolingual settings. There is substantial evidence for this claim that includes studies with participants of different ages, speaking different languages, and using different empirical methodologies (e.g., Poarch & Van Hell, 2012a ; Rodriguez-Fornells, Rotte, Heinze, Nösselt, & Münte, 2002 ; Thierry & Wu, 2007 ; Van Heuven, Schriefers, Dijkstra, & Hagoort, 2008 ). For example, in a study with Russian-English bilinguals conducted by Marian, Spivey, and Hirsch (2003) , eye movements were recorded during an English-only task. Participants saw a display of four pictures and were asked to make an eye movement towards the one that was named, but pictures whose Russian names sounded like the English target word elicited a significant number of initial eye movements. Thus, an instruction to look at the “marker” elicited eye movements to a picture of a stamp, called “marka” in Russian. Therefore, in spite of all instructions and all test materials being in English and despite the English context in which the experiment was conducted, performance of the bilinguals was influenced by Russian, a language not required for the task or by the context.

Other evidence for dual-language activation was found in a go/no-go task using event-related potentials (ERP). Wu and Thierry (2012) asked Chinese–English bilinguals to make visual form judgments on shapes (go), while withholding a response when an English word was shown (no-go). During the task, a shape appeared on the screen and participants were instructed to press one of two buttons to indicate whether it was a circle or a square (go) while intervening English words were presented with instruction to refrain from pressing either button (no-go). Critically, some of these to-be-ignored English words resembled the sound of the Chinese translations of the words for “circle” (yuán) or “square” (fāng). For example, one of the stimuli was the English word ‘reason’, for which the Chinese translation is ‘yuán yin’. On these trials, participants were influenced by the irrelevant word and chose the button press associated with the word rather than the shape, similar to the interference in a Stroop task. In the control condition, there was no phonological or semantic relation between the English words, their translation equivalent in Chinese, and the subsequent shape. Event-related potential amplitudes revealed greater inhibitory processing in the conflict trials than in the control condition. The authors interpreted this pattern as indicating parallel access to translation equivalents in the native language during involuntary second language processing in a non-verbal task. At the same time, this dual activation also necessitated rapid inhibition of the first language (Chinese) to avoid adversely affecting performance in the nonverbal task.

It is the joint activation of the two languages that creates the need for the recruitment of EF in ordinary linguistic tasks by bilinguals. Crucially, multitasking is also strongly dependent on EF. The central argument, therefore, is that bilingual language use is a special case of multitasking and the claim is that the use of EF to manage attention to two languages strengthens EF processes for other purposes. By implication, therefore, bilinguals should be better multitaskers than monolinguals. Consistent with this argument, a large body of evidence has shown that all the EF components are enhanced in bilinguals, both for children (for meta-analysis, see Adesope, Lavin, Thompson, & Ungerleider, 2010 ), and adults (for review, see Bialystok, Craik, Green, & Gollan, 2009 ). Bilingual children and adults perform better than monolinguals in tasks that involve conflict induced by task-irrelevant information such as the flanker task ( Carlson & Meltzoff, 2008 ; Costa, Hernández, & Sebastián-Gallés, 2008 ; Emmorey, Luk, Pyers, & Bialystok, 2008 ; Marzecová, Asanowicz, Krivá, & Wodniecka, 2013 ; Nicolay & Poncelet, 2012 ; Pelham & Abrams, 2014 ; Poarch & Van Hell, 2012b ), the Simon task ( Bialystok, Craik, Klein, & Viswanathan, 2004 ; Martin-Rhee, & Bialystok, 2008 ), and the Stroop task ( Bialystok, Craik, & Luk, 2008 , Blumenfeld & Marian, 2011 ; Hernández, Costa, Fuentes, Vivas, & Sebastián-Gallés, 2010 ). These tasks require conflict resolution to deal with the distracting cues, efficient switching between different trials types, and maintenance of the relevant rules for the task in working memory.

These bilingual advantages in controlling attention, particularly when there is conflict, appear not to depend on experience in using language, that is, language production. Research on preverbal infants has shown that even in early stages of language acquisition, exposure to more than one language affects nonverbal attentional processing. In an eye-tracking study, Kovács and Mehler (2009) compared 7-month-old bilingual and monolingual infants on a simple visual attention task. The bilingual infants had been exposed to two parental languages in the home since birth whereas monolingual infants had been exposed to only one language. In three experiments, infants were taught to respond to a speech stimulus cue or a visual pattern cue in anticipation of a reward (a puppet) that would appear on the left or the right side of a screen. Both groups of infants performed equally well predicting the position of a visual reward in the learning phase. For the experimental phase, the location of the reward was switched and the infants had to redirect their anticipatory looks to the opposite side of the screen. The switched location necessitated suppression of the first learned response and switching to a new response. The bilingual infants managed to update their predictions as to where the visual reward would appear while the monolingual infants did not. The authors interpreted their results as indicating accelerated development of general executive functioning in these infants stemming from perceiving and processing utterances from two language sources from birth.

Evidence for an attentional advantage in bilingual infants extends to linguistic tasks. In a study by Weikum et al. (2007) , 6-month old infants could discriminate between an individual speaking English from the same individual switching and speaking an unfamiliar language, French, on the basis of visual facial cues only but failed to make the discrimination by 8 months old. In contrast, infants being raised in homes in which they were exposed to both English at French were successful in making this discrimination and could detect when the speaker switched languages by watching the silent video. This result indicates that, compared to monolingual children, bilingual infants maintain the ability to visually discriminate between languages based on their need to separate and process multiple languages. A recent study by Sebastián-Gallés, Albareda-Castellot, Weikum, and Werker (2012) extended this research to determine whether familiarity with the language or a more general attentional discrimination was responsible. They assessed the ability of 8-month-old Spanish-Catalan infants to visually discern language switches from French to English and from English to French from facial cues only while watching silent videos. Spanish-Catalan bilingual and Spanish and Catalan monolingual infants were shown silent video clips of a bilingual adult reading sentences in French or English (the same materials used in the study by Weikum et al., 2007 ) until infants were habituated. Following habituation, the infants' looking times were recorded to the speaker continuing to speak in the same language or switching to the other language. Importantly, neither of these languages was familiar to any of the infants. The authors found that the Spanish-Catalan bilingual infants could discriminate between English and French but the Spanish and Catalan monolingual infants could not. The authors interpreted these results as indicating that bilinguals who need to process dual-language input from birth accrue general cognitive advantages and that these advantages stem from the need to separate languages during language acquisition. The primary evidence of this cognitive advantage in infancy is in better attentional processing.

Evidence for superior non-verbal executive function and conflict resolution in bilingual children has been reported in a number of studies (e.g., Adi-Japha, Berberich-Artzi, & Libnawi, 2010 ; Poulin-Dubois, Blaye, Coutya, & Bialystok, 2011 ; Yang, Yang, & Lust, 2011 ). For example, Carlson and Meltzoff (2008) administered executive function tasks to children who were English monolinguals, English-Spanish bilinguals, or English-speaking children enrolled in a second-language immersion elementary school. The bilingual children showed better performance on the executive function tasks than did both other groups. Critically, this advantage did not extend to suppressing a motor response on delay-of-gratification tasks (response inhibition) but was significant on conditions in which memory and inhibition of attention to a prepotent response was required (interference suppression; cf. Martin-Rhee & Bialystok, 2008 ). This study also highlighted the conclusion that enhanced executive functioning may require sustained bilingual exposure beyond the 6-month period that the group of immersed children had experienced (see also Poarch & Van Hell, 2012b , for similar results with children who had been immersed for approximately 15 months).

Bilingualism and multitasking

Few of the studies investigating bilingualism and executive functioning have used paradigms traditionally considered to be tests of multitasking, but there are some exceptions. Bialystok (2011) reported a study in which 8-year-old children who were monolingual or bilingual completed two tasks in which they were asked to classify either sounds or pictures as belonging to the category of animals or musical instruments. Children in both groups completed both tasks equivalently, but when the tasks were combined and children were required to perform both at the same time, the bilingual children maintained a significantly higher level of performance than did the monolingual children. Thus it appears that they were more skilled in managing two concurrent tasks when there was interference and competition between them. Our interpretation is that this task is easier for bilingual children because they function in a constant state of linguistic multitasking.

Unlike the limited research investigating multitasking in bilinguals, there is a larger literature examining language processing and switching in bilinguals, situations that inherently involve multitasking. Like monolinguals, bilinguals need to construct contextually-driven speech plans for speech production. Additionally, however, bilinguals also need to selectively attend to target language structures while resolving competition from the other language and monitor the languages to allow shifting between them if necessary. Green (1998) proposed an inhibitory control mechanism that prevents the non-target language from intruding into the speech plan (see also Costa, 2005 ; Kroll, Bobb, Misra, & Guo, 2008 ). At a later stage during lexical retrieval, the activation of competitors in the non-target language is reduced through inhibitory processes to resolve competition and enable selection only within the target language. According to Green, bilinguals continuously call upon this inhibitory control mechanism and so accrue massive amounts of experience in control, the accumulation of which may alter the neural organization underlying executive functions (e.g., Abutalebi, 2007 ; Abutalebi et al., 2008 , 2012; see also Stocco, Yamasaki, Natalenko, & Prat, 2014 , for a model combining bilingualism, executive functions and neural information processing).

These changes in executive function are found not only in behavioral performance but also in brain structures involved in the executive function system. Specifically, bilinguals have greater grey matter density in the left putamen ( Abutalebi et al., 2013 ) and the left inferior parietal lobule ( Mechelli et al, 2004 ) than monolinguals. Abutalebi and colleagues (2012) explored whether bilinguals control their languages relying on a neural system that is shared with general cognitive processes. In a number of neuroimaging studies, they found that both language control and cognitive control were subserved by the dorsal anterior cingulate cortex (ACC) in bilinguals, both regions central to the executive function. Critically, when comparing bilinguals and monolinguals, bilinguals showed more efficient use of the ACC during the monitoring of cognitive conflict in non-verbal tasks, a finding replicated by Gold et al. (2013) with older bilinguals. Abutalebi and colleagues interpreted these results as indicating better adaptation to conflicting situations based on the bilinguals' need to control sustained language conflict. Hence, bilingualism induces experience-driven neurocognitive changes from which bilinguals may benefit processing in non-verbal domains.

The important finding in these studies is bilingual language control is subserved by the same neural regions as those engaged by domain-general executive control. Evidence for this conclusion comes from language switching and nonverbal task-switching studies (see Abutalebi & Green, 2007 , 2008 ; Luk, Green, Abutalebi, & Grady, 2012 , for reviews). Task-switching paradigms traditionally invoke a local switch cost, calculated as the difference in reaction times between task-switch trials and non-switch trials (e.g., Monsell, 2003 ; see also reviews by Koch, Gade, Schuch, & Philipp, 2010 ; Schneider & Anderson, 2010 ). Furthermore, the magnitude of this local switch cost depends on the relative difficulty of the two tasks. Specifically, when the two tasks vary in difficulty, local switch costs are generally smaller when switching from the easy task into the more difficult task than when switching from the difficult task into the easier one. Allport, Styles, and Hsieh (1994) explain this asymmetry in terms of the task-set inertia hypothesis , in which switching costs are assumed to stem from the need to retrieve task-sets inhibited in previous trials (see also Vandierendonck, Liefooghe, & Verbruggen, 2010 ; Yeung & Monsell, 2003 ). Performing a difficult task requires relatively less inhibition of the easier tasks than does the ability to perform an easy task while attempting to inhibit interference from the more difficult task. Hence, in the subsequent trial either weak or strong inhibition that had been implemented in the previous trial needs to be overcome. This difference in the level of inhibition required in switching between tasks that vary in difficulty gives rise to an asymmetrical switch cost. In contrast, for tasks that are comparable in difficulty and therefore require similar levels of inhibition of the irrelevant task to execute, switches in both directions are similar in magnitude, creating a symmetrical switch cost.

Meuter and Allport (1999) extended this line of research to examine task-switching between two languages. They found that low-proficient bilinguals showed asymmetrical switch costs with larger switch costs when switching from the weaker, more difficult language (L2) into the dominant, easier language (L1) than vice versa, a finding that is in line with results from nonverbal task-switching research. The larger the proficiency difference between languages, the larger the difference in the magnitude of inhibition between the switch from L1 to L2 (easier switch since less inhibition of L2 is necessary while performing in L1) and from L2 to L1 (more difficult switch because of the need for stronger inhibition of L1 while performing in L2). It would follow, therefore, that bilinguals with more balanced proficiency in the two languages would show more symmetrical switching costs because the two tasks are more equivalent in difficulty. This pattern was reported in a study by Costa and Santesteban (2004) , in which highly proficient Catalan-Spanish bilinguals switched between languages and demonstrated comparable switching costs when switching from L1 to L2 and from L2 to L1.

The language studies described above demonstrate the constant effort exerted by bilinguals to switch between their two languages. What happens when bilinguals need to switch between two nonverbal tasks? Studies comparing monolinguals and bilinguals have shown smaller switch costs in these tasks for bilinguals than for monolinguals, indicative of more efficient task shifting processes ( Garbin et al., 2010 ; Prior & Gollan, 2011 ; Prior & MacWhinney, 2010; Wiseheart, Viswanathan, & Bialystok, in press ). However, in a recent review Bobb and Wodniecka (2013) suggest that the costs in verbal and non-verbal switching tasks may not necessarily be related to an inhibitory mechanism but rather to the persistence of activation of the task that has become irrelevant (see Philipp, Gade, & Koch, 2007 ). Thus, bilinguals may develop an increased ability to resist this interference from the previous task when switching to the new task. This ability in highly-proficient bilinguals may also extend to switching between two established languages and a third less proficient language (see Costa, Santesteban, & Ivanova, 2006 , for symmetrical switching costs in highly proficient trilinguals).

Task switching is the basis of multitasking, but task switching itself is not a dichotomous concept in which pairs of trials require either the same (non-switch) or a different (switch) task rule. Salvucci and colleagues ( Salvucci, Taatgen, & Borst, 2009 ; Salvucci & Taatgen, 2008 , 2011 ) proposed a continuum based on the time span between switches. In this scheme, concurrent tasks are those tasks that are performed essentially simultaneously with more time-sequential tasks spread along the continuum, such as switching between reading an email and writing a response. The cognitive demands of concurrent tasks depend on such processes as shifting and allocating resources, attentional control, and inhibition of the less-relevant task. These processes are decreasingly involved as time between switches increases along the continuum. Thus, greater time between tasks would presumably involve less EF.

Just as task switching can be considered on a continuum, so too can bilingualism. Gradations in bilingualism can be described in terms of either the relative proficiency between the two languages (as in the difference between partial bilinguals and highly-balanced bilinguals) or between the number of languages the individual speaks (as in the difference between bilinguals and trilinguals). If the EF advantages found for bilingualism reflect practice, then greater practice through either degree of bilingualism or number of languages should induce a greater advantage. Regarding degree of bilingualism for children, Bialystok and Barac (2012) reported that more time in an immersion education program was significantly associated with greater benefit on EF tasks, specifically a flanker task or task-switching paradigm. Using a different approach, Poarch and Van Hell (2012b) compared the performance of children who were monolinguals, second-language learners, bilinguals, or trilinguals and found significantly better performance by multilinguals than monolinguals, with second-language learners partway between these groups. This pattern is consistent with the notion of a continuum of language experience, although there was no effect of the number of languages on EF outcomes.

To summarize, the argument is that bilingual experience enhances the set of EF processes that are central for multitasking so by implication, bilingual children should be better multitaskers than monolinguals. However, two kinds of evidence are needed to support this argument. First, recent studies have challenged the assumption that bilingualism leads to enhanced EF, the key mechanism for these effects. For example, Duñabeitia et al. (2014) compared monolingual and bilingual children across a wide range of ages performing verbal and non-verbal Stroop tasks based on EF and found no significant difference between groups. However, little information was provided about the language abilities of these children, so it is important to confirm there is a bilingual EF advantage in a group for whom language proficiency is known. Second, if the bilingual advantage in EF is essentially a practice effect in which these EF processes are used for language switching, then being more bilingual should result in a greater EF advantage. Therefore, a more detailed description of bilingualism is required. Although the present study did not directly compare monolingual and bilingual children in a multitasking paradigm, it addressed these two issues to evaluate the argument that bilingualism should be associated with better multitasking.

To investigate the hypothesis of an EF advantage in bilingual children and its relation to degree of bilingualism, the present study examined four groups of children – monolinguals, partial bilinguals, balanced bilinguals, and trilinguals – for their performance on a standard EF task, namely, the flanker task. The hypotheses were that (a) carefully selected balanced bilinguals would outperform monolinguals on this EF task, confirming a bilingual advantage in an essential aspect of EF, and (b) greater practice with bilingualism would lead to greater benefit, so that balanced bilinguals would outperform unbalanced bilinguals on this task and that trilingual children would outperform bilinguals.

Participants

Participants were 203 children, 8- to 11-year old, who attended public elementary schools. Sixty children were English monolinguals (31 girls and 29 boys), 44 children were being educated in French but used it only in school so were partially bilingual (26 girls and 18 boys), 60 were fully bilingual (28 girls and 32 boys), and 39 were trilingual (21 girls and 18 boys). The children's mean age was 9.5 years ( SD = 0.9; range = 8.1 – 11.9 months).

Parents provided signed consent and completed a Language and Social Background Questionnaire (LSBQ; Luk & Bialystok, 2013 ) describing the home language environment and proficiency in each language. The partial bilinguals were all native speakers of English and had been learning French for an average of 2.0 years ( SD = 0.7). The bilingual children lived in homes in which English was not the primary language but English was used outside the home and in school, and the trilinguals spoke two languages at home in addition to English. Parents were asked to rate their children's daily language usage on a set of 7-point scales that extended from “All English” (1) to “Only other language” (7). An average score of 4 indicates that home communication was divided equally between the languages. The mean score across these scales for monolinguals was 1.2 ( SD = 0.2) and for partial bilinguals 1.6 ( SD = 0.6), indicating that the homes functioned primarily in English. The mean scores in the bilingual and trilingual groups were 3.0 ( SD = 1.2) and 3.3 ( SD = 1.4), respectively, indicating a more balanced use of English and the other language(s), F (3, 199) = 63.5, p < .001. Tukey HSD posthoc analyses indicated that bilinguals and trilinguals had significantly more use of non-English languages in their homes than monolinguals and partial bilinguals, p s < .001, with no difference between bilinguals and trilinguals, p = .52, and no difference between monolinguals and partial bilinguals, p = .15. Socioeconomic status (SES) was indexed by parents' education using a 5-point scale (1 = not completed high school; 2 = high school diploma; 3 = some postsecondary education; 4 = bachelor's degree; 5 = graduate or professional degree). There were no differences between groups, F s < 2, p > .12. Background measures are reported in Table 1 .

Mean scores (and standard deviations) for background measures by language group.

The bilingual and trilingual groups were heterogeneous; there were 22 non-English languages for the bilinguals including Bengali (1), Cantonese (3), Farsi (2), French (5), German (3), Gujarati (4), Hindi (3), Italian (2), Kutchi (1), Lithuanian (1), Mandarin (3), Polish (2), Punjabi (5), Russian (3), Serbian (1), Spanish (2), Tagalog (4), Tamil (4), Telugu (2), Twi (4), Urdu (2), and Vietnamese (3). There were 20 non-English languages for the trilinguals including Arabic (2), Cantonese (3), French (29), Greek (2), Gujarati (4), Hindi (3), Italian (3), Japanese (1), Khmer (4), Mandarin (4), Polish (3), Punjabi (4), Spanish (1), Somali (4), Tajik (1), Tamil (3), Teochew (1), Twi (3), Vietnamese (2), and Yoruba (1).

Participants completed all tasks in a single 30-minute session. Children were tested individually in a quiet space in their schools by a trained experimenter. Following the session, children were thanked for their help and given stickers as a small gift.

Peabody Picture Vocabulary Test

The Peabody Picture Vocabulary Test (PPVT-III, Dunn & Dunn, 1997 ) is a standardized test of receptive vocabulary. Participants are shown test plates of four pictures, one of which the experimenter names. The pictures are black-and-white line drawings of objects, actions, or concepts and participants are required to indicate the named image. The plates become increasingly difficult as the test proceeds. Testing is discontinued once the participant makes 8 errors in a given block of 12 trials. The raw scores are then converted to standard scores based on the participant's age.

Raven's Colored Progressive Matrices

The Raven's test ( Raven, Raven, & Court 1998 ) is a measure of nonverbal visuospatial reasoning. Two arrays of colored pictures are shown to the participant: one picture forms a pattern and a second one depicts potential components of the pattern. The participant must indicate the picture in the second array that best matches the picture in the first array. Results are calculated as standard scores, which are corrected for age.

Executive functions task

The executive functions task was a modified flanker task ( Eriksen & Eriksen, 1974 ). Children were asked to indicate the direction in which a target chevron in the middle of an array of five chevrons was pointing by pressing one of two mouse buttons positioned on either side of the computer. There were four types of trials. In baseline trials, only one chevron was shown in the middle of the screen and participants indicated if it was pointing left or right by pressing the mouse key on the left or right side of the computer. In neutral trials, the middle chevron was flanked by two diamonds. In congruent trials, the flanking chevrons pointed in the same direction as the target, but in incongruent trials, the target and flanking chevrons pointed in opposite directions. Trials began with a 500 ms fixation prior to stimulus onset. The trial terminated either after a subject response or a time-out after 3000 ms. All trials within each block were counterbalanced with right/left responses. The experiment was presented in five blocks. First was a block of 24 baseline trials followed by one block of 24 neutral trials. After this was a mixed block of 24 congruent and 24 incongruent trials with presentation of congruent and incongruent trials generated randomly by the E-prime program. After this, there was another block of 24 neutral trials and then another block of 24 baseline trials. Only RTs of correct responses were included in the analysis.

Results from demographic background, English vocabulary, and nonverbal intelligence measures are presented in Table 1 . One-way ANOVAs showed that the children in the four groups did not differ in English vocabulary and nonverbal intelligence, F s < 1.2, p s > .30.

Mean response times (RT) and mean accuracy rates were calculated for each condition of the flanker task. Incorrect responses (5.1% for the baseline condition, 5.8% for the neutral condition, 3.9% for the congruent condition, and 8.1% for the incongruent condition) were excluded from the RT analysis. Outliers with RTs shorter than 200 ms or longer than 2000 ms and 2.5 SD below or above the mean (4.8 % for the baseline condition, 4.6% for the neutral condition, 4.7% for the congruent condition, and 5.1% for the incongruent condition) were also excluded from the RT analyses. Accuracy and RT data are presented in Table 2 . Accuracy was at ceiling so no further analyses were conducted.

Mean RT and accuracy scores (and standard deviations) in flanker task by language group.

For RT scores, separate one-way ANOVAs on baseline and neutral trials to establish whether there were speed of processing differences between groups showed no significant group effect, F s < 1. RTs for the two trial types of interest in the flanker task, the congruent and incongruent trials were analyzed using repeated measures mixed ANOVAs with trial type (congruent and incongruent) as within-group variable and language group (monolinguals, partial bilinguals, bilinguals, and trilinguals) as between-group variable. The RT analysis yielded a main effect of trial type, F (3, 199) = 225.20, η 2 = .58, p < .001, no effect of language group, F (3, 199) < 1, η 2 < .01, p = .73, and an interaction between trial type and language group, F (3, 199) = 11.5, η 2 = .06, p < .001. Tukey HSD posthoc analyses showed that bilinguals and trilinguals were significantly faster at resolving conflict than monolinguals and partial bilinguals, ps < .02, on the incongruent trials. Critically, bilinguals and trilinguals did not differ significantly from each other, nor did monolinguals and partial bilinguals, ps > .50. The results indicate that the bilinguals and trilinguals were better at resolving conflict than the monolinguals and partial bilinguals. This interpretation was confirmed by a separate one-way ANOVA on the conflict magnitudes (incongruent condition RTs– congruent condition RTs), F (3, 199) = 11.50, η 2 = .15, p < .001.

The purpose of this study was to establish differences between monolingual and bilingual children performing a standard executive function task and relating that performance to the executive control demands of the task (mixed conflict block vs. neutral block) and the degree to which children were bilingual (partial bilinguals, bilinguals, or trilinguals). The results support the hypothesis for EF advantages in bilingual children performing a nonverbal conflict task but only partially support the practice hypothesis in which these advantages would be calibrated to the degree of bilingualism.

The novel design feature of the study was to extend previous research that had focused on monolinguals and bilinguals and include children who were partial bilinguals and speakers of more than two languages. The prediction was that these would be additional points on a continuum in which greater EF advantages would be found with greater bilingual experience. Importantly, children in the four groups did not differ in global reaction times (RT), indicating equal task monitoring abilities across groups. However, the bilingual and trilingual children showed significantly less interference in the incongruent condition and thus were better at resolving conflict than were the monolinguals and partial bilinguals, with no significant differences within these pairs. Therefore, the results from our study provide no evidence to support the idea that controlling three languages instead of two languages provides an additional boost to the efficacy of the attentional control system. Similarly, there is no evidence that being partially bilingual was sufficient to distinguish these children from monolinguals on this nonverbal EF task. Thus, if there is an experience-based gradient that is associated with EF performance, it was not properly captured in the four groups included in this study. Instead, the results are in line with a more dichotomous view in which children who are fully bilingual or trilingual demonstrate an EF advantage over those who are not.

Speakers who use more than one language on a regular basis need to control which language to choose in a given context and prevent interference from the language not in use. This process makes all language use by bilinguals a model for linguistic multitasking. The current study demonstrated that more experience in bilingual language processing was associated with better performance on an EF task. Although the EF task used in this study was not a measure of task switching or multitasking, it incorporates the essential elements of those tasks, namely, selection, inhibition, and response shifting.

Two important results from the present study support our interpretation regarding multitasking. First, the proficient bilingual and trilingual children performed significantly better than the monolingual children on the conflict condition of the task. Some recent research has reported that these effects were not found and that there was no difference between monolingual and bilingual children on such tasks (e.g., Duñabeitia et al., 2014 ). Thus, the present results add to the body of literature demonstrating these advantages in bilingual children (see Adesope et al., 2010 for review and meta-analysis).

Second, the results provide a hint regarding why some studies may not find these differences between monolingual and bilingual children. The majority of the literature provides little documentation of the language abilities and language experiences of children assigned to the monolingual or bilingual groups. Instead, researchers rely on global assessments from parents, teachers, or others with little constraint on how the decisions were made. Consequently, it is conceivable that not all children in the monolingual group are completely monolingual and not all children in the bilingual group are completely bilingual. As seen in the present study, partially bilingual children performed comparably to monolingual children. Therefore, without adequate control over designations as monolingual or bilingual, no group differences would be expected to emerge.

Our interpretation of these results is that the lifelong use of two or more languages can be viewed as a constant form of multitasking. Multitasking has become commonplace in our daily lives; depending on the environment, it has been shown to have positive and negative effects. Driving a car, for example, and at the same time texting on a mobile phone may put the driver and other motorists and pedestrians in danger. Doctors in hospitals and air-traffic controllers, in contrast, may need to multitask in order to manage and perform all their tasks efficiently. There is, furthermore, evidence that some individuals display the ability to perform complex multitasking with very little cost compared to most others who show decreased performance (see Watson & Strayer, 2010 , for so-called supertaskers). The experience of bilingualism may be a facilitatory form of multitasking, all the more so since a linguistic experience of juggling and controlling two languages evidently has an enhancing effect on nonverbal executive processing. As such, bilingualism demonstrates the capacity for human multitasking.

Finally, it remains to be seen in what way the experience of life-long bilingualism takes effect at different levels of multitasking, in other words, whether bilingualism can offset the cognitive cost of multitasking at higher levels of performance compared to monolinguals, and if so, how much bilingual experience is necessary to have such differential effects. As Adler and Benbunan-Fich (2012) have shown, participants' improvement on task performance during multitasking at lower levels, attributed to increased arousal and, consequently, enhanced alertness induced by the multitasking environment, is lost at higher levels of multitasking due to growing between-task interference. One may adduce that bilinguals should be able to maintain an enhanced state of alertness at even higher levels of multitasking than monolinguals. Such differences will, however, be strongly linked to the quantity and quality of bilingual language input, particularly in children, in whom both language and EF are still developing. How often a bilingual individual regularly switches between languages and how proficient this individual is in each language will have a major impact on the development of EF and, by extension, on multitasking capacity.

• Constant use of two languages creates a situation of multitasking for bilingual children
• Multitasking recruits the executive control system
• New data are presented showing a bilingual advantage in an executive control task
• Full bilingualism was necessary for this advantage to emerge

Acknowledgments

This work was funded by grant R01HD052523 from the US National Institutes of Health to EB. We are grateful to Geoff Sorge for his contribution to this study.

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